Calibration methods for placement machines incorporating on-head linescan sensing

ABSTRACT

A method of calibrating a pick and place machine having an on-head linescan sensor is disclosed. The calibration includes obtaining z-axis height information of one or more nozzle tips via focus metric methods, including a Fourier transform method and a normalized correlation method. Additionally, other physical characteristics such as linear detector tilt, horizontal scale factor, and vertical scale factor are measured and compensated for in the process of placing the component. Nozzle runout, another physical characteristic, is also measured by a sinusoidal curve fit method, and the resulting Z-height calibration data is used to later place the component.

COPYRIGHT RESERVATION

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BACKGROUND OF THE INVENTION

The present invention relates to pick and place machines. Moreparticularly, the present invention relates to a method of calibratingpick and place machines.

Pick and place machines are used by the electronics assembly industry tomount individual components on printed circuit boards. These machinesautomate the tedious process of placing individual electrical componentson the circuit board. In operation, pick and place machines generallypick up individual components from a component feeder or the like, andplace the components in their respective positions on a circuit board.

During the placement operation, it is generally necessary for the pickand place machine to look at, or image, a given component prior toplacement in order to adjust the orientation of the component for properplacement. Such imaging allows precise adjustments to be made to thecomponent's orientation, such that the component will be accuratelyplaced in its desired position.

One standard type of pick and place machine uses a shadowing sensor,such as a LaserAlign® sensor available from CyberOptics® Corporation ofGolden Valley, Minn. In a shadowing sensor, the object under test isrotated, and the effective width of the shadow (or an image of theshadow) is monitored on a detector. The dimensions of the object can becomputed by monitoring the width of the shadow (or the shadow image).During start-up, the pick and place machine is calibrated so that anypositional output from the sensor is mathematically related to the pickand place machine coordinate system. Once a correlation between the pickand place machine and the sensor output is known in X and Y, the pickand place machine can accurately place the object under test in itsintended (X, Y) location on, say, a printed circuit board. There arealso disclosed methods of calibrating the Z-height of a nozzle, so thatthe pick and place machine can repeatably place the object onto theintended place at the correct Z height. However, the methods disclosedfor calibrating pick and place machines in (X, Y) and in Z are specificto the type of sensor in the pick and place machine.

Another type of pick and place machine uses an on-head linescan sensorto image the component while the placement head is traveling. An on-headsensor, as used herein, refers to a sensor which travels with theplacement head in at least one dimension, so as to sense the orientationof the component while the component travels to the circuit board. Thisis in contrast to off-head systems, where the component is transportedto a stationary station to sense the orientation of the component, andfrom there, the component is transported to the circuit board. Alinescan sensor, as used herein, is an optical sensor comprised of aplurality of light sensitive elements that are arranged in a line suchthat the sensor acquires a single line of the image in a given timeperiod. By translating the linescan sensor relative to the entirecomponent and storing a plurality of the acquired lines, the componentimage is realized and X, Y and θ orientation is then calculated usingthis scanned image.

Placement machines incorporating on-head linescan sensing technology arevery flexible in the types of components that they can place. Theon-head linescan sensor is able to directly image components such aschip capacitors, Quad Flat Packs (QFP), TSOP, Ball Grid Arrays (BGA),CSP, and flip-chips. The video output of the linescan camera allows avideo processor to compute the orientation of the component. Based onknowledge of the desired orientation of the component and the presentorientation, the pick and place machine corrects the orientation of thecomponent and places it on a printed circuit board. The linescan imagecan also provide inspection information about the component to beplaced. Also, placement machines incorporating on-head linescan sensingare very fast compared to off-head sensing technologies since the stepof visiting a fixed inspection station to measure pick-up offset errorsis eliminated. To increase the accuracy of pick and place machines usingon-head linescan sensing technology, however, careful calibration of thelinescan sensor and its physical relationship to other parts of theplacement machine should be performed.

SUMMARY OF THE INVENTION

A method of calibrating a pick and place machine having an on-headlinescan sensor is disclosed. The calibration includes obtaining z-axisheight information of one or more nozzle tips via focus metric methods,including a Fourier transform method and a normalized correlationmethod. Additionally, other physical characteristics such as lineardetector tilt, horizontal scale factor, and vertical scale factor aremeasured and compensated for in the process of placing the component.Nozzle runout, another physical characteristic, is also measured by asinusoidal curve fit method, and the resulting Z-height calibration datais used to later place the component.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a top plan view of a pick and place machine.

FIG. 2 is a perspective view of a pick and place head in accordance withan embodiment of the present invention.

FIG. 3 is a block diagram of a method of calibrating a pick and placemachine in accordance with an embodiment of the present invention.

FIG. 4 is a chart of contrast vs. nozzle Z-position.

FIG. 5 is a diagrammatic view of a rotated linescan sensor.

FIG. 6 is a diagrammatic view of sheared linescan images.

FIG. 7 is a diagrammatic view of a calibration target.

FIG. 8 is a diagrammatic view of a linescan sensor and calibrationtarget in the X-Y coordinate system of the linescan sensor stage.

FIG. 9 is a diagrammatic view of a linescan sensor stage coordinatesystem as it relates to the coordinate system of a pick and placemachine.

FIG. 10A is a diagrammatic view of components A and B as measured in acoordinate system of a linescan sensor.

FIG. 10B is a diagrammatic view of components A and B as measured in acoordinate system of a pick and place machine.

FIG. 11 is a diagrammatic view illustrating nozzle runout.

FIG. 12 is a top plan view illustrating nozzle tip positions at variousangular orientations associated with the nozzle runout shown in FIG. 8.

FIG. 13 is a pair of charts showing nozzle tip position along the X′ andY′ axes vs. nozzle angle θ.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

FIG. 1 is a top plan view of pick and place machine 31 in accordancewith an embodiment of the present invention. Pick and place machine 31is adapted to mount a variety of electrical components such as chipresistors, chip capacitors, flip-chips, Ball Grid Arrays (BGA), QuadFlat Packs (QFP), and connectors on a workpiece 32 such as a printedcircuit board.

As various methods are disclosed, it will be apparent that there arethree relevant coordinate systems. Interrelationships between all threemust be known in order to accurately and repeatably place a component inan intended location. Coordinates of the scanned image are denoted witha single prime after the coordinate (i.e. (X′,Y′,Z′)). Coordinates ofthe linescan sensor stage are denoted without any prime notation (i.e.(X,Y,Z)); the pick and place coordinate system is denoted by a doubleprime notation (i.e. (X″,Y″,Z″)) and the coordinate system of a targetis denoted in a triple prime labeling convention (i.e. (X″′,Y″′,Z″′)).

The individual components are picked up from feeders 34 which aredisposed on opposite sides of conveyor 33. Feeders 34 can be known tapefeeders, or any other suitable device.

Pick and place head 37 is adapted to releasably pick up components fromfeeders 34 and transport such components to their respective mountinglocations upon workpiece 32. Head 37 will be described in greater detailwith respect to FIG. 2. Head 37 is movably disposed upon carriage 41,and is coupled to drive motor 42 via a ballscrew or other appropriatemeans. Thus, energization of motor 42 causes displacement of head 37 inthe Y″ direction along carriage 41, as indicated by arrow 20. Motor 42is coupled to encoder 43 which provides a Y″-axis position signal to acontroller 39.

Skipping ahead to FIG. 2, Linescan sensor 64 views the component fromits underside, so a scanned image from sensor 64 may include detail ofthe underside of the component. The underside is typically the mostdetailed portion of the component, with fine pitch balls, columns, orother connection means may be present. The linescan sensor 64 also hasthe advantage of a variable field of view, with a variable resolution,so that as more detail is needed, the resolution and field of view maybe appropriately adjusted.

Carriage 41 is mounted upon a pair of guide rails 46, and is movablealong the X″ axis, as indicated by arrow 22. Carriage 41 is coupled todrive motor 49 such that energization of motor 49 causes a displacementof carriage 41, and head 37 along the X″ axis. Encoder 51 is coupled tomotor 49 to provide a X″-axis position signal to the controller 39.

Pick and place machine 31 also includes controller 39 which receives theencoder position signals from encoders 42, 51, receives linescan imageinformation from sensor 64 (shown in FIG. 2), and receives fiducialimage data from camera 92 (shown in FIG. 2). As will be described ingreater detail later in the specification, controller 39 computesphysical characteristics for calibrating pick and place machine 31.

Other sorts of linescan sensors are adaptable for use with the presentmethods for calibration. For example, some high-capacity pick and placemachines have a turret system with a rotating head which sequentiallyplaces components it picks up on a plurality of nozzles, all of whichrotate around a central point in the rotating head. As for traditionalX,Y translation gantry pick and place machines, some have recently beenmodified so that they have a small degree of movement in one dimensionwhile the gantry is fixed in another orthogonal direction. Furthermore,it is understood that for any linescan sensor to scan an object ofinterest, there must either be movement of the sensor while the objectis stationary, movement of the object of interest while the sensor isstationary, or movement of both sensor and object at the same time.

FIG. 2 is a perspective view of placement head 37 in accordance with anembodiment of the present invention. As can be seen, placement head 37includes two vacuum pick-up nozzles 62, fiducial sensing camera 92,on-head linescan sensor 64, and linescan sensor stage 88. Nozzles 62 arecoupled to pickup units 84 such that components 86A and 86B held bynozzles 62 can be translated up and down and rotated about theirrespective nozzle axes. Although two nozzles 62 are shown in FIG. 2, anysuitable number of nozzles, including one nozzle, can be used topractice embodiments of the present invention.

Linescan sensor 64 is movably supported upon linear stage 88, such thatlinescan sensor 64 can move in the Y direction as indicated by arrow 21.A linear motor (not shown) provides the drive, but any mechanicalarrangement for moving the stage 88 is acceptable. Fiducial camera 92 isdisposed on head 37 and measures registration marks, or fiducials, onthe workpiece. The locations of the fiducials are used in order tocompute the placement location correction, as well as facilitatecalibration, as will be described in greater detail later in thespecification.

In order to calibrate pick and place machine 31, it is generallynecessary to measure a number of physical characteristics of the pickand place machine. With these physical characteristics and knowledge ofthe mathematical relationship between the sensor coordinate system, theline scan stage coordinate system and the pick and place machinecoordinate system, a processor in the system can compute instructionsfor moving the head to finely and accurately place the component in theintended location (this process is called “compensating” the position ofthe component). These characteristics include the Z-axis height of eachnozzle tip on the placement head relative to some reference position ofa Z position encoder in the pick and place machine, the location of eachnozzle on the placement head, the effective axis of the linescan sensor,the horizontal scale factor of the linescan sensor, the vertical scalefactor of the linescan sensor, and the runout of each nozzle.

All embodiments of the present invention utilize a linescan sensor forcalibration, it is preferred that the first step in the calibrationprocess is location of the Z-axis heights of the nozzle tips, such thatlater calibration steps can be performed at the focal plane of thelinescan sensor, and thus be performed more accurately. Once the nozzleZ-heights are established, each nozzle can be adjusted for the properZ-axis position so that all components and calibration targets are inbest focus (i.e. positioned in the focal plane) when scanned by thelinescan sensor.

FIG. 3 shows one method of calculating the Z-heights in accordance withan embodiment of the present invention. The method shown in FIG. 3 canbe considered an autofocus method for reasons which will become apparentduring the description of FIG. 3. Prior to beginning of the method ofFIG. 3, an illumination type is chosen that will highlight the sharpedges of each nozzle tip. Linescan sensors can employ sophisticatedcombinations of various illumination types, and a description of suchillumination can be found in co-pending application Ser. No. 09/432,552filed Nov. 3, 1999 entitled ELECTRONICS ASSEMBLY APPARATUS WITH IMPROVEDIMAGING SYSTEM. Once the scanned image is acquired, a focus metricmethod is applied to the scanned image to provide a measure of the focusof the nozzle tips and finally, to compute the z elevation of the nozzleat which the nozzle tips are in best focus. Two embodiments for thefocus metric method will be presented here, but other methods can beequally suitable.

The procedure begins at block 100 by raising each nozzle so that eachtip is known to be above the Z location of the plane of best focus forthe linescan sensor. Next, a scan of all nozzle tips is performed bytranslating linescan sensor 64 in the Y direction and acquiring a singleimage of all the nozzle tips in a scanned image, as indicated by block102.

At block 104, a focus metric method is applied to the scanned images ofthe nozzle tips and the result is stored along with some indication ofthe presently set Z height. Although two embodiments for focus metricmethods are described herein, it is understood that any method whichidentifies an optical Z height corresponding to the best focus of thenozzles will be adequate.

In a first embodiment of the focus metric method, a two dimensionalFourier transform is performed on the scanned images of the nozzle tips.Since the scanned images of the nozzle tips have a significanthigh-frequency content, a Fourier transform will permit analysis of thestrength of the high frequency components, and thus the sharpness of theimages. Other means for identifying high frequency portions of a scannedimage may also be employed.

At block 108, the focus metric result from block 104 is compared to thepreviously stored focus metric results from images at previous nozzle Zpositions. In this first embodiment of the focus metric method, theamplitude of selected high frequency spatial components in the Fouriertransform of the scanned image is the measure of best focus. Theamplitudes of the high frequency components for each nozzle increasesuntil local maxima are achieved which corresponds roughly to the optimalZ height for best focus. After reaching the maxima, the amplitudes ofthe high frequency components begins to decrease. When these monitoredamplitudes begin to decrease, the presently set Z height is less thanthe optimal Z height. As indicated in FIG. 3, if the Z height is not yetless than the optimal Z height, the nozzles are lowered at block 112 andthe process starts again at block 102.

Otherwise, the process continues at block 110, where a fourth orderpolynomial is fit to the amplitude data in order to interpolate anoptimal Z height for each nozzle that results in the highest contrast,and thus best focus. Curve fitting suppresses noise, and allows theselection of the optional focus point to be computed. Any suitable curvefitting method can be used to fit the results from the “focus-metric”method to any suitable mathematical model. The result of the curvefitting preferably facilitates interpolation of the Z height position ofbest focus for each nozzle from the “focus-metric” data.

Functions other than Fourier Transform amplitude may be used to measurethe sharpness of the edges of the nozzles in the scanned image, and thisinformation can then be used to compute when the image of the nozzletips is in best focus.

An alternate focus metric method can be used in block 104 in FIG. 3. Inthis alternative focus metric, a template (i.e. expected image) of eachnozzle tip is compared to the nozzle tip in the scanned image. Thetemplate can be constructed in software or a previously recorded imageof the nozzle tip that is in sharp focus can be used. The normalizedcorrelation algorithm returns a score indicating the quality of thetemplate match, and the score is stored as a measure of the focus ateach Z-height. When the correlation score is maximized, the scannedimage of nozzle tips is in best focus. Various types of auto-focusmethods, other than the normalized correlation and the Fourier transformmethod are equally suitable.

The next preferred step in the calibration process is to make theeffective axis of the linear detector within the linescan sensorperpendicular to the linescan sensor's direction of motion. If there isa tilt in this effective axis, then all images will appear to besheared. FIG. 5 shows the effective axis 65 of the linear detectortilted at a greatly exaggerated angle θ_(d) with respect to the X axis.The Y axis in this figure is the direction of motion for linescan stage88. Linescan stage 88 is omitted in FIG. 5 for clarity, but is shown inFIG. 2.

FIG. 6 shows the sheared images 87A and 87B of components 86A and 86B,respectively. Also, labeled in FIG. 6 is the X′-Y′ coordinate system ofthe linescan sensor 64 as it appears in a captured video image. Theprocedure that follows uses the linescan sensor to scan a calibrationtarget of known dimension that has been picked up by one of the nozzles.The detector tilt is calculated from this image of the calibrationtarget.

If the detector tilt θ_(d), calculated below, is larger than theallowable tolerance, the linescan sensor housing is rotated in the X-Yplane on its mechanical mount. The rotation is accomplished byunscrewing bolts which fix sensor stage 88 into place on head 37 orother suitable mechanical means. Then, the procedure of scanning,calculating the detector tilt, and rotating the linescan sensor housingrepeats until the detector tilt is within tolerance limits.Additionally, the horizontal and vertical scale factors of the linescansensor are measured in the same procedure.

To measure the detector tilt, vertical scale factor and horizontal scalefactor of the linescan sensor, a calibration target of known dimensionis used. Preferably, this target is made by high precisionphotolithographic techniques. An example of a suitable calibrationtarget 128 is shown in FIG. 7. Features 130A through 130F are knownsize, shape, and location in the X″′-Y″′ coordinate system. Thesefeatures are also referred to as fiducial marks.

Another type of calibration target 128 that has been successfully usedhas an orthogonal grid of squares patterned on it.

In general, the image of the features or grid will be sheared, rotatedand have an offset in the linescan image.

In FIG. 8 calibration target 128 is rotated by an amount θ_(g) withrespect to the X axis.

Referring now back to FIGS. 5 and 6, we see that points in the linescanimage are transformed to points in the coordinate frame of stage 88 bythe relationship $\begin{matrix}{\begin{bmatrix}X \\Y\end{bmatrix} = {\begin{bmatrix}{h\quad \cos \quad \theta_{d}} & 0 \\{h\quad \sin \quad \theta_{d}} & v\end{bmatrix}\begin{bmatrix}X^{\prime} \\Y^{\prime}\end{bmatrix}}} & (1)\end{matrix}$

Where h and v are the horizontal and vertical scale factors,respectively, and Equation (1) accounts for both scale and shear.

FIG. 8 shows linescan sensor 64 prior to obtaining an image ofcalibration target 128. Calibration target is held by one of the vacuumnozzles (not shown). Calibration target is shown rotated by an amountθ_(g). In the stage coordinate frame, the positions of features 130Athrough 130F, ignoring offsets, are given by the rotation equation:$\begin{matrix}{\begin{bmatrix}X \\Y\end{bmatrix} = {\begin{bmatrix}{\cos \quad \theta_{g}} & {\text{-}\sin \quad \theta_{g}} \\{\sin \quad \theta_{g}} & {\cos \quad \theta_{g}}\end{bmatrix}\begin{bmatrix}X^{\prime\prime\prime} \\Y^{\prime\prime\prime}\end{bmatrix}}} & (2)\end{matrix}$

Equating equations (1) and (2) gives: $\begin{matrix}{{\begin{bmatrix}{h\quad \cos \quad \theta_{d}} & 0 \\{h\quad \sin \quad \theta_{d}} & v\end{bmatrix}\begin{bmatrix}X^{\prime} \\Y^{\prime}\end{bmatrix}} = {\begin{bmatrix}{\cos \quad \theta_{g}} & {\text{-}\sin \quad \theta_{g}} \\{\sin \quad \theta_{g}} & {\cos \quad \theta_{g}}\end{bmatrix}\begin{bmatrix}X^{\prime\prime\prime} \\Y^{\prime\prime\prime}\end{bmatrix}}} & (3)\end{matrix}$

To compute the linear detector tilt, horizontal scale factor, andvertical scale factor, a geometric transformation is used. One geometrictransformation, known as the affine transformation, can accommodatetranslation, rotation, scaling and shear. Further information about theaffine transformation is provided in the monograph by George Wolbergentitled, “Digital Image Warping” (IEEE Computer Society Press, 1990).

Points in the X′-Y′ linescan sensor image coordinate frame are mappedinto the X″′-Y″′ calibration target coordinate frame, preferably by thefollowing affine transformation: $\begin{matrix}{\begin{bmatrix}X^{\prime\prime\prime} \\Y^{\prime\prime\prime}\end{bmatrix} = {{\begin{bmatrix}\alpha & \beta \\\gamma & \delta\end{bmatrix}\begin{bmatrix}X^{\prime} \\Y^{\prime}\end{bmatrix}} + \begin{bmatrix}X_{0}^{\prime} \\Y_{0}^{\prime}\end{bmatrix}}} & (4)\end{matrix}$

where (X′₀, Y′₀) is the offset of the calibration target 128 origin andα, β, γ, δ describe the rotation, scale, and shear of the calibrationtarget image. The location (X′, Y′) of each feature 130A through 130F isfound in the linescan image by the normalized correlation method.Equation (4) is repeated for each feature 130A through 130F. Theparameters α, β, γ, δ, X′₀, Y′₀ are then found by a known method such asthe method of least squares, although other interpolation methods aresuitable.

Substituting equation (4) into equation (3) gives: $\begin{matrix}{{\begin{bmatrix}{h\quad \cos \quad \theta_{d}} & 0 \\{h\quad \sin \quad \theta_{d}} & v\end{bmatrix}\begin{bmatrix}X^{\prime} \\Y^{\prime}\end{bmatrix}} = {{\begin{bmatrix}{\cos \quad \theta_{g}} & {\text{-}\sin \quad \theta_{g}} \\{\sin \quad \theta_{g}} & {\cos \quad \theta_{g}}\end{bmatrix}\begin{bmatrix}\alpha & \beta \\\gamma & \delta\end{bmatrix}}\begin{bmatrix}X^{\prime} \\Y^{\prime}\end{bmatrix}}} & (5)\end{matrix}$

Again, the offsets are ignored since it is desired to only compute thedetector tilt, horizontal scale factor, and the vertical scale factor.

If equation (5) holds for all $\begin{bmatrix}X^{\prime} \\Y^{\prime}\end{bmatrix}$

then: $\begin{matrix}{\begin{bmatrix}{h\quad \cos \quad \theta_{d}} & 0 \\{h\quad \sin \quad \theta_{d}} & v\end{bmatrix} = {\begin{bmatrix}{\cos \quad \theta_{g}} & {\text{-}\sin \quad \theta_{g}} \\{\sin \quad \theta_{g}} & {\cos \quad \theta_{g}}\end{bmatrix}\begin{bmatrix}\alpha & \beta \\\gamma & \delta\end{bmatrix}}} & (6)\end{matrix}$

Writing out the “northeast” equation of (6) gives:

β cos θ_(g)−δ sin θ_(g)=0  (7)

Solving equation (7) for the tilt of the calibration target, θ_(g),gives: $\begin{matrix}{\theta_{g} = {\tan^{- 1}( \frac{\beta}{\delta} )}} & (8)\end{matrix}$

By using standard trigonometric identities, equation (6) becomes$\begin{matrix}{{{\frac{1}{\sqrt{\beta^{2} + \delta^{2}}}\begin{bmatrix}\delta & {- \beta} \\\beta & \delta\end{bmatrix}}\begin{bmatrix}\alpha & \beta \\\gamma & \delta\end{bmatrix}} = \begin{bmatrix}{h\quad \cos \quad \theta_{d}} & 0 \\{h\quad \sin \quad \theta_{d}} & v\end{bmatrix}} & (9)\end{matrix}$

Solving equation (9) for detector tilt θ_(d), gives: $\begin{matrix}{\theta_{d} = {\tan^{- 1}( \frac{{\alpha\beta} + {\gamma\delta}}{{\alpha\delta} - {\beta\gamma}} )}} & (10)\end{matrix}$

The horizontal and vertical scale factors are given by:

h={square root over (α²+γ²)},  (11)

v={square root over (β²+δ²)}  (12)

Another method for computing detector tilt θ_(d) can be performed byimaging a target with a clearly delineated pattern on the target, suchas a square or a rectangle. Once the scanned image of the target (whichincludes the pattern) is acquired, the slope of each of the linesegments forming the pattern can be computed with commercially availablemachine vision software. With knowledge of the equation of at least twoadjacent line segments in the rectangle, the angle, θ_(d), between thetwo line segments can be computed and compared to the expected anglebetween the line segments. Alternatively, one can compute θ_(d) and thescale factors by performing a transformation on at least three points,each point formed by the intersection of the line segments. Finally, thestage 88 is be mechanically adjusted by the angle θ_(d), therebycompensating for the initial detector stage tilt in subsequentmeasurements.

Once the linear detector tilt has been removed, the mapping of thelinescan stage coordinate frame into the placement machine coordinateframe is determined. FIG. 9 shows an example where the coordinate axisof the on-head linescan sensor stage is tilted relative to the X″-Y″axes of the placement machine. (In the present placement machineembodiment, the placement head moves both in the X″ and Y″ axes. Inother placement machine embodiments, the placement head may move in onlythe X″ or Y″ axis).

The procedure begins by picking up components labeled 86A and 86B asshown in FIG. 2. For simplicity, components 86A and 86B will be referredto as components A and B, respectively, hereinafter. For thiscalibration step, the components are preferably machined rectangularblocks. However, normal electrical components can also be used.Components A and B are then scanned by linescan sensor 64 and the centerpositions of components A and B are calculated. After components A and Bhave been scanned, they are placed on a target substrate. Fiducialcamera 92 is then sequentially positioned over components A and B andtheir locations on the substrate are measured in the placement machinecoordinate frame. Fiducial camera 92 travels and also measures in theplacement machine coordinate frame because it is mounted to theplacement head.

FIG. 10A shows the locations (X′_(A), Y′_(A)) and (X′_(B), Y′_(B)) ofcomponents A and B, respectively, as measured by linescan sensor 64 inthe single prime linescan coordinate system. Line 132 between these twopoints makes an angle ε with respect to the Y′ axis. FIG. 10B shows thelocations (X″_(A), Y″_(A)) and (X″_(B) and Y″_(B)) of components A andB, respectively, as measured by fiducial camera 92 in the double primecoordinate system of placement machine 31. Line 134 between these twopoints makes an angle ω with respect to the Y″ axis. For this example,the two coordinate frames are rotated with respect to one another by anamount φ as given by equation (13). Equations (14) and (15) giveexpressions for ε and ω.

φ=ε−ω  (13)

$\begin{matrix}{ɛ = {\tan^{- 1}( \frac{X_{B^{\prime}} - X_{A^{\prime}}}{Y_{B^{\prime}} - Y_{A^{\prime}}} )}} & (14) \\{\omega = {\tan^{- 1}( \frac{X_{B^{\prime}} - X_{A^{\prime}}}{Y_{B^{\prime}} - Y_{A^{\prime}}} )}} & (15)\end{matrix}$

Converting measurements made in the prime coordinate frame of linescansensor 64 (X′,Y′) into the double prime coordinate frame of placementmachine 31 (X″,Y″) by a translation and rotation is given by thefollowing equation $\begin{matrix}{\begin{bmatrix}X^{\prime\prime} \\Y^{\prime\prime}\end{bmatrix} = {{\begin{bmatrix}{\cos \quad \phi} & {\text{-}\sin \quad \phi} \\{\sin \quad \phi} & {\cos \quad \phi}\end{bmatrix}\begin{bmatrix}X^{\prime} \\Y^{\prime}\end{bmatrix}} + \begin{bmatrix}X_{0}^{\prime} \\Y_{0}^{\prime}\end{bmatrix}}} & (16)\end{matrix}$

The translation amounts X′₀ and Y′₀ may be calculated by substitutingmeasured locations of either component A or B into equation (16). Doingthis for the measured location of components A gives:

X′ ₀ =X″ _(A) −X′ _(A) cos φ+Y′ _(A) sin φ  (17)

Y′ ₀ =Y″ _(A) −X′ _(A) sin φ−Y′ _(A) cos φ  (18)

The accuracy of pick and place machine 31 is also improved by measuringthe exact locations of the nozzles and measuring any mechanical runoutof the nozzles as they are rotated. Runout refers to the offset of thenozzle tip from its effective axis of rotation, as measured in the planeof the nozzle tip. FIG. 11 shows a side view of a nozzle 62 with runoutand the dotted line view of the same nozzle after it has been rotated180°. To measure the nozzle locations and the associated runout, thenozzles are scanned and then their locations are computed by thenormalized correlation method described earlier. The nozzles are thenincremented in the θ direction and the procedure of scanning andmeasuring their locations by using the normalized correlation method isrepeated until the nozzles have been rotated through 360°. FIG. 12 showsan example of one nozzle tip location for various nozzle angles. Thecircles labeled 1 through 6 on FIG. 12 are the nozzle tip images forthis example. FIGS. 13A and 13B show the X′ and Y′ locations of thenozzle tip plotted against the θ position of the nozzle. Nozzle tiplocations 1 through 6 are also labeled in FIGS. 13A and 13B. The nozzlerunout axes and angles can be found from a best-fit sinusoidal curve tothe X′ and Y′ locations as described below. FIGS. 13A and 13B also showthese best-fit sinusoidal curves. The equations for the tip position ofnozzle number k are given by:

X′ _(k) =X′ _(ck) +R _(k) cos(θ_(k)−ξ_(k))  (19)

Y′ _(k) =Y′ _(ck) +R _(k) sin(θ_(k)−ξ_(k))  (20)

where the center of rotation for nozzle number k is given by thecoordinate (X′_(ck), Y′_(ck)) and the radius of revolution is given byR_(k). The angle of the nozzle is θ_(k) and ξ_(k) is an angular offset.

To solve equations (19) and (20) for the nozzle center position, theradius, and the angular offset, the following parameters a_(k) and b_(k)are defined

a _(k) =R _(k) cos ξ_(k)  (21)

b _(k) =R _(k) sin ξ_(k)  (22)

Using the standard trigonometric angle-difference formulas, equations(19) and (20) become $\begin{matrix}{\begin{bmatrix}X_{k}^{\prime} \\Y_{k}^{\prime}\end{bmatrix} = {{\begin{bmatrix}{\cos \quad \theta_{k}} & {\sin \quad \theta_{k}} \\{\sin \quad \theta_{g}} & {\text{-}\cos \quad \theta_{k}}\end{bmatrix}\begin{bmatrix}a_{k} \\b_{k}\end{bmatrix}} + \begin{bmatrix}X_{ck}^{\prime} \\Y_{ck}^{\prime}\end{bmatrix}}} & (23)\end{matrix}$

The method of least squares is then used to compute a_(k), b_(k), andthe center of rotation for each nozzle. The radius of revolution and theangular offset are then given by

R _(k) ={square root over (a_(k) ²+b_(k) ²)}  (24)

$\begin{matrix}{\xi_{k} = {\tan^{- 1}( \frac{b_{k}}{a_{k}} )}} & (25)\end{matrix}$

When a component must be rotated after having been measured by linescansensor 64 and prior to placement, the difference in nozzle centerposition for the two angles is computed. The difference is then appliedto the correction amount measured by the linescan sensor. Furtherinformation regarding the correction amount calculation can be found inthe co-pending United States patent application listed above.

From FIGS. 13A and 13B, it should be apparent that nozzle runout couldbecome a large error source when the component must be rotated through alarge angle because it was picked up in a different orientation than itis to be placed on the printed circuit board. It is typical to rotate acomponent approximately −90°, 90°, or 180° prior to placement. To reducethe amount of runout correction necessary, components may be pre-rotatedto their approximate placement orientation before scanning with thelinescan sensor. This pre-rotation can take place while the nozzle isretracted in a position for scanning, or the pre-rotation can take placewhile the nozzle is being retracted after part pick-up.

Although the present invention has been described with reference topreferred embodiments, workers skilled in the art will recognize thatchanges may be made in form and detail without departing from the spiritand scope of the invention. In particular, the calibration methods ofthe present invention can be readily expanded to multiple nozzles.

What is claimed is:
 1. A method of calibrating a pick and place machinehaving at least one nozzle, the method comprising: scanning the at leastone nozzle with an on-head linescan sensor to provide a scanned image;calculating a physical characteristic of the at least one nozzle basedat least in part on the scanned image; placing a component based atleast in part on the calculated physical characteristic; and wherein thenozzle is displaced in a Z direction after the step of scanning the atleast one nozzle, and wherein the step of scanning the at least onenozzle is repeated to provide a plurality of additional scanned images,where the physical characteristic is a Z-height of the at least onenozzle.
 2. The method of claim 1 further comprising performing afocus-metric method on the scanned image and on the plurality ofadditional scanned images, the result of the focus metric method used tocompute the Z-height.
 3. The method of claim 2 where the focus-metricmethod includes analyzing a strength of high frequency components in thescanned image and in the plurality of scanned images.
 4. The method ofclaim 3 where the step of analyzing the strength of high frequencycomponents includes performing a Fourier transform.
 5. The method ofclaim 3 where the step of analyzing the strength provides a plurality ofmeasures of sharpness of the scanned image and the plurality ofadditional scanned images, and further where the step of computing theZ-height includes interpolating between the plurality of measures ofsharpness.
 6. The method of claim 5 where the Z-height is computed frominterpolating the plurality of measures of correlation.
 7. The method ofclaim 2 where the focus metric method includes comparing the scannedimage and the plurality of additional scanned images to a template imageto provide a plurality of measures of correlation, where the pluralityof measures of correlation are used to compute the Z-height.
 8. Themethod of claim 1 further comprising picking up a component with the atleast one nozzle and positioning the component on a Z-axis based on theZ-height.
 9. A method of calibrating a pick and place machine having atleast one nozzle, the method comprising: scanning the at least onenozzle with an on-head linescan sensor to provide a scanned image;calculating a physical characteristic of the at least one nozzle basedat least in part on the scanned image; placing a component based atleast in part on the calculated physical characteristic; and wherein thelinescan sensor is mounted on a placement head, where the physicalcharacteristic is a position of the at least one nozzle on the placementhead.
 10. The method of claim 9 where the position is indicated relativeto two orthogonal axes.
 11. The method of claim 9 where the position iscomputed as a function of a linescan coordinate system, a stagecoordinate system and a pick and place coordinate system.
 12. The methodof claim 9 further comprising picking up a component with the at leastone nozzle and positioning the component relative to a pick and placecoordinate system based on the position.
 13. The method of claim 9 wherethe placement head includes an additional nozzle, where the physicalcharacteristic indicates a position of the at least one nozzle and ofthe additional nozzle.